Special Sessions

Below, the special sessions as organized as part of the IEA/AIE 2013 conference are listed. The submission instructions for the special sessions are the same as those for the main track of the IEA/AIE conference (see the paper submission part). Note however that some special sessions might have a deadline after the official conference deadline. Therefore, when you intend to submit a paper to one of the special sessions after the official deadline, please submit the paper to the corresponding organizers via email as the Easychair system will be closed.

Business
Process
Intelligence
(BPI)
is
a
new
is
a
research
area
that
is
attracting
the
attention
of
both
scientific
and
industrial
research
communities.
It
refers
to
the
application
of
various
reasoning-­‐based
and
intelligent
methodologies
to
the
field
of
business
process
management
for
supporting
companies
in
their
daily
activities
and
improving
their
performances
in
terms
of
the
quality
of
the
services
provided
to
their
business
partners
and
customers.
In
particular,
the
main
goal
of
BPI
is
to
provide
a
better
understanding
of
techniques,
methodologies
and
algorithms
for
modeling
and
handling
multiple
companies’
processes,
both
at
design-­‐time
and
run-­‐time.
This
complex
activity
is
mainly
based
on
different
operational
steps:
process
identification,
process
analyses,
process
simulation
and
static
and
dynamic
process
improvement.
As
a
consequence
of
its
intrinsic
complexity,
BPI
brings
together
practitioners
and
researchers
from
different
research
communities
such
as
business
process
management,
information
systems
research,
business
administration,
software
engineering,
artificial
intelligence,
process
mining,
and
data
mining
who
share
an
interest
in
the
analysis
of
business
processes
and
process-­‐aware
information
systems.
The
objective
of
this
special
issue
is
to
highlight
an
ongoing
research
BPI
as
well
as
its
applications
on
various
domains.
The
list
of
topics
that
are
relevant
to
the
BPI
workshop
includes
the
following,
but
is
not
limited
to:

The special session on Innovations in Computation and Applications brings together researchers working across this field to share their experience and
discuss advanced techniques. Prospective authors are invited to submit original papers to the Special Session.

Indicative Topics/Areas:

Within the scope of this session, areas of interest include, but are not limited to:

Machine Learning, a branch of artificial intelligence, is a scientific discipline concerned with the design and development of algorithms that allow computers to evolve behaviours based on empirical data, such as from sensor data or databases. Some of the latest Machine Learning applications are: speech recognition, traffic and fault classification, surface quality prediction in laser machining, network security and bioinformatics, enterprise credit risk evaluation, and so on. This special session is focused on its applications to manufacturing processes and production systems.

Topics of interest

The scope of this special session covers the following Machine Learning related techniques:

Decision Support

Process and System Control

System Identification and Modelling

Optimisation

Signal or Image Processing

Vision or Pattern Recognition

Systems Integration

Internet Tools

Human-Machine Interface

Time Series Prediction

Motion Control and Power Electronics

Biomedical Engineering

Virtual Reality

Reactive Distributed AI

Data Mining

Data Visualisation

Intelligent Information Retrieval

Bio-inspired Systems

Autonomous Reasoning

Intelligent Agents

Multiclassifiers

and should search for its industrial applications to manufacturing processes and productions systems like:

Manufacturing Technologies

Manufacturing monitoring and control

Production control and optimization

Fault Diagnosis and maintenance

Inventory management

Robotics and assembly technologies

Electronics

Manufacturing Systems design and manufacture

Power and Energy generation and distribution

Production system design and control

Paper submission

Authors are invited to submit their papers in English of up to 10 single spaced pages, presenting the results of original research or innovative practical applications relevant to the conference. Practical experiences with state-of-the-art AI methodologies are also acceptable when they reflect lessons of unique value to the conference attendees. Shorter works, up to 6 pages, to be presented in 10 minutes, may be submitted as short papers representing work in progress or suggesting possible research directions. All paper submissions will be done electronically, as indicated in the instructions on the conference web site http://iea-aie2013.few.vu.nl. All papers will be peer reviewed and final copies of papers for inclusion to the conference proceedings will be published in a bound volume by Springer-Verlag (formatting instructions are available at http://www.springer.de/comp/lncs/authors.html) in their Lecture Notes in Artificial Intelligence (http://www.springer.com/lncs) series. Referees will be asked to nominate papers for a Best Paper Award to be announced at the conference. All papers will be automatically considered for publication in an expanded form in selected international journals.

Machine Learning has experienced a rapid development in recent years which has allowed it to leave the academic environment and become a technique commonly used in the real world. It is in this context that the importance of certain problems, that some researchers were beginning to glimpse, have become apparent. One of such problem is the unbalanced data. In classification, this problem occurs when some classes have far fewer instances than others. In regression, when some regions of the input space have a density of examples much lower than others. This problem is prevalent in many real-world applications: failure prediction, fraud/intrusion detection, gene and protein annotation, text classification, but there are many others. The aim of this special session is to bring together researchers and practitioners that are dealing with this challenging problem, from both the development of new methods and techniques, and the application of methods to real-world problems.

Paper submission

Authors are invited to submit their papers in English of up to 10 single spaced pages, presenting the results of original research or innovative practical applications relevant to the conference. Practical experiences with state-of-the-art AI methodologies are also acceptable when they reflect lessons of unique value to the conference attendees. Shorter works, up to 6 pages, to be presented in 10 minutes, may be submitted as short papers representing work in progress or suggesting possible research directions. All paper submissions will be done electronically, as indicated in the instructions on the conference web site http://iea-aie2013.few.vu.nl. All papers will be peer reviewed and final copies of papers for inclusion to the conference proceedings will be published in a bound volume by Springer-Verlag (formatting instructions are available at http://www.springer.de/comp/lncs/authors.html) in their Lecture Notes in Artificial Intelligence (http://www.springer.com/lncs) series. Referees will be asked to nominate papers for a Best Paper Award to be announced at the conference. All papers will be automatically considered for publication in an expanded form in selected international journals.

Recommender systems are software systems that aim to support users in different types of decision making scenarios related to the selection of items from large and sometimes complex information spaces. Items are recommended on the basis of the preferences that have been expressed by the users either in an explicit or in an implicit fashion. Due to the continuously growing size and complexity of information systems, recommender systems are already a key technology in many different application scenarios (e.g., netflix.com, amazon.com, and yahoo.com). Recommender systems include applications which range from e-commerce to social networking and mobile platforms and are implemented on the basis of an increasing variety of techniques and algorithms having their origin in the basic concepts of content-based filtering, collaborative filtering, knowledge-based recommendation and different variants thereof. The topics of this special session include (but are not limited to):

A huge number of textual document collections are available on the WEB that are stored in organizational databases. Some of them are public and may include web pages, news articles and technical reports whereas some are private such as electronic mails. Automatic Text Classification (TC) aims to classify these documents by content into the most relevant category. Grouping of public documents is needed to assist the search engines for effective retrieval. The importance of this task has recently become even more crucial due to the exponential increase in the number of documents in electronic forms. Spam filtering which identifies and stops unwanted emails, email foldering which aims to categorize electronic messages, sentiment classification which recognizes whether a given sentence or document expresses a positive or negative opinion and biomedical information extraction are some of the other key tasks that necessitate the use of robust text classification systems. Because of these essential needs, TC has become an attractive field for many researchers in the last decade. The aim of this special session is to discuss the recent developments in the field and consider novel ideas that will pave the way for future research.

Paper submission due January 4, 2013

Topics of Interest

The topics of intereset include but not restricted to the following items:

Binary and multi-class text classification

Uni-label and multi-label text classification

Term (word) weighting

Term selection

Feature extraction to define novel features

n-grams, compound features (termsets), syntactic phrases as features

Classification techniques

Evaluation measures

Imbalanced text classification

Thresholding

Ensemble methods

Paper Submission

Authors are invited to submit their papers in English of up to 10 single spaced pages, presenting the results of original research or innovative practical applications relevant to the conference. Practical experiences with state-of-the-art AI methodologies are also acceptable when they reflect lessons of unique value to the conference attendees. Shorter works, up to 6 pages, to be presented in 10 minutes, may be submitted as short papers representing work in progress or suggesting possible research directions. All paper submissions will be done electronically, as indicated in the instructions on the conference web site http://iea-aie2013.few.vu.nl. All papers will be peer reviewed and final copies of papers for inclusion to the conference proceedings will be published in a bound volume by Springer-Verlag (formatting instructions are available at http://www.springer.de/comp/lncs/authors.html) in their Lecture Notes in Artificial Intelligence (http://www.springer.com/lncs) series. Referees will be asked to nominate papers for a Best Paper Award to be announced at the conference. All papers will be automatically considered for publication in an expanded form in selected international journals.

Safety is of paramount importance in industry. With the increase in complexity of industrial system or plants safety consideration can consume a great deal of time both in the design and operation stages. Therefore, there are many potential benefits in developing innovative decision support systems to help to improve the efficiency, correctness and completeness of different safety-related tasks to avoid accidents from happening or to mitigate against major consequences.

This session deals with new technologies for intelligent algorithms and architectures for image and signal processing. This special session combines advanced research themes in multimedia systems, image processing, signal processing, as well as their applications. Topics of interest include, but are not limited to: